/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

#ifndef TENSORFLOW_LITE_DELEGATES_GPU_CL_KERNELS_CONV_WEIGHTS_CONVERTER_H_
#define TENSORFLOW_LITE_DELEGATES_GPU_CL_KERNELS_CONV_WEIGHTS_CONVERTER_H_

#include "tensorflow/lite/delegates/gpu/cl/cl_command_queue.h"
#include "tensorflow/lite/delegates/gpu/cl/cl_kernel.h"
#include "tensorflow/lite/delegates/gpu/cl/kernels/conv_common.h"
#include "tensorflow/lite/delegates/gpu/cl/kernels/gpu_operation.h"
#include "tensorflow/lite/delegates/gpu/common/status.h"
#include "tensorflow/lite/delegates/gpu/common/types.h"

namespace tflite {
namespace gpu {
namespace cl {

class ConverterToConvWeights : public GPUOperation {
 public:
  ConverterToConvWeights(const OperationDef& definition,
                         const ConvWeightsDescription& conv_weights_desc);
  absl::Status BindArguments(ArgumentsBinder* args) override;
  int3 GetGridSize() const override;

  // Move only
  ConverterToConvWeights(ConverterToConvWeights&& operation);
  ConverterToConvWeights& operator=(ConverterToConvWeights&& operation);
  ConverterToConvWeights(const ConverterToConvWeights&) = delete;
  ConverterToConvWeights& operator=(const ConverterToConvWeights&) = delete;

 private:
  std::string GetConverterToConvWeightsCode(
      const OperationDef& op_def,
      const ConvWeightsDescription& conv_weights_desc);

  ConvWeightsDescription conv_weights_desc_;
};

// We expect src BHWC tensor and we assume that B is O, H = H, W = W, C is I
// as dst we expect Tensor with storage type BUFFER and
// dst.b * dst.h * dst.w * dst.c = AlignByN(src.b, 4) * src.h * src.w
// AlignByN(src.c, 4)
ConverterToConvWeights CreateConverterToConvWeights(
    const OperationDef& definition,
    const ConvWeightsDescription& conv_weights_desc);

}  // namespace cl
}  // namespace gpu
}  // namespace tflite

#endif  // TENSORFLOW_LITE_DELEGATES_GPU_CL_KERNELS_CONV_WEIGHTS_CONVERTER_H_
